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Think about all the challenges that go into interpretation: a human sitting in a booth, listening to live speech in one language and somehow smoothly repeating it in another language, sometimes for hours at a time. Then imagine our interpreter is working at a specialized conference where the speaker is using arcane terminology, forcing them to come up with rarely used words and phrases at a moment’s notice.

Add a computer into the mix, and our interpreter’s job gets easier, right? Not so fast, said Graham Neubig, an assistant professor in the Language Technologies...
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New resource can be used to build text-to-speech systems for hundreds of languages

by Byron Spice | Monday, December 10, 2018

It’s the Christmas season, which means that beloved Bible verses are being read and recited innumerable times — and in a vast number of languages. The Bible’s global reach as evidenced this time of year has enabled a Carnegie Mellon University professor to create a language resource that could enhance communication in hundreds of languages.

By tapping online text and audio recordings of the New Testament in more than 700 languages, Alan Black, a professor in CMU’s Language Technologies Institute, has created a dataset that can be used to build text-to-speech computer systems and...
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Students and faculty at Carnegie Mellon University's School of Computer Science are collaborating with the digital media intelligence firm Meltwater to advance the state of the art in artificial intelligence education and research using the...
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LTI faculty and students are featured heavily at the 2018 conference of the North American chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT 2018). The conference includes 15 papers with at least one LTI author, with 23 members of the LTI community represented in total. Additionally, two LTI faculty members – assistant professors Graham Neubig and Yulia Tsvetkov – will be leading tutorials at the conference.

NAACL HLT, now in its 16th year, is one of the world’s premier conferences in the fields of computation linguistics and...
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In March, 2005, a team of LTI researchers launched a spoken dialog system aimed at providing after-hours information to users of the Allegheny County public transit system. 13 years later, the system has handled over 200,000 calls, producing data that’s been used in over 22 doctoral theses and more than 250 publications outside the CMU community. And now, that data is publicly available to researchers everywhere in hopes of continuing to advance the state of the art in this ever-evolving field.

For the third year in a row, Carnegie Mellon University's forecasts of national influenza activity have proven to be the most accurate among all forecasting systems evaluated by the U.S. Centers for Disease Control and Prevention.

For the third year in a row, students from the Language Technologies Institute were honored as among the best in the BioASQ Biomedical Semantic Question Answering Challenge (BioASQ 2017).

Khyathi Chandu, Aakanksha Naik, and Aditya Chandrasekar, all Master of Language Technology students enrolled in the Question Answering course during the spring semester, picked up on the work of previous LTI teams to compete in the competition, extending the codebase with the goal of improving performance on “ideal answer” (summarization) questions.

A student in the LTI’s Master of Language Technologes program was recently honored with the Outstanding Paper Award at the 2017 Conference of the European Chapter of the Association for Computational Linguistics (EACL 2017). Adhiguna Kuncoro’s paper “What Do Recurrent Neural Network Grammars Learn About Syntax?” was one of just three out of the 119 accepted long papers to receive the honor at EACL 2017, one of the most prestigious conferences on natural language processing worldwide.